Failure mode and effects analysis (FMEA) is a widely used technique for identifying, evaluating, and eliminating potential failures in production, system, and process. The traditional FMEA ranks the failure modes according to risk priority numbers (RPN), which are obtained by the multiplications of the crisp values of risk factors, such as occurrence (O), severity (S), and detection (D). However, the traditional FMEA is criticized for mishandling uncertain information and calculating RPN unreasonably. To overcome the above deficiencies, this study presents an advanced FMEA method combined with interval 2-tuple linguistic variables (ITLV) and technique for order preference by similarity to ideal solution (TOPSIS). In the proposed method, the evaluations given by different FMEA members based on their different linguistic term sets are represented by ITLVs, which are feasible and valid variables to effectively deal with uncertain information. The TOPSIS method is used to rank the risk priorities of failure modes by comprehensively considering all of risk factors. Finally, an application case is provided to illustrate the validity and robustness of the proposed method.

故障模式和影响分析（FMEA）是一种广泛使用的技术，用于识别，评估和消除生产，系统和过程中的潜在故障。传统的FMEA根据风险优先级数字（RPN）对故障模式进行排名，该风险优先级数字是通过将危险因素的明晰值（例如发生（O），严重性（S）和检测（D））相乘而获得的。但是，传统的FMEA被批评为错误地处理了不确定的信息并不合理地计算了RPN。为了克服上述缺陷，本研究提出了一种结合间隔2元组语言变量（ITLV）的先进FMEA方法和通过类似于理想解决方案（TOPSIS）的顺序偏好技术。在建议的方法中，不同的FMEA成员根据其不同的语言术语集进行的评估以ITLV表示，这是有效且有效地处理不确定信息的变量。TOPSIS方法用于通过综合考虑所有风险因素来对故障模式的风险优先级进行排序。最后，提供了一个应用案例来说明所提方法的有效性和鲁棒性。